Challenges and Advancements in Speaker Diarization and Recognition for Naturalistic Data
Offered By: Center for Language & Speech Processing(CLSP), JHU via YouTube
Course Description
Overview
Explore the cutting-edge advancements in speaker diarization and recognition for naturalistic data in this insightful lecture by John Hansen. Delve into the world of speech technology and its applications in extracting knowledge and assessing engagement content. Learn about the impact of big data, machine learning, and voice-enabled systems on speech and speaker recognition. Discover how these technologies are applied to real-world scenarios, including child learning spaces and NASA APOLLO lunar missions. Gain insights into automatic audio diarization, speech recognition, and speaker recognition techniques. Examine the assessment of child-teacher conversational interactions, including keyword and "WH-word" analysis. Understand the challenges and solutions in processing massive datasets, such as the expanded Apollo-11 corpus containing 150,000 hours of mission data. Explore the interdisciplinary applications of this research in speech/language technology, STEM/science, team-based research, and education/historical archiving. Uncover how these advancements contribute to understanding collaborative work and learning, as well as their role in accomplishing mankind's greatest scientific and technological challenges.
Syllabus
Challenges and Advancements in Speaker Diarization & Recognition for Naturalistic Data–John Hansen
Taught by
Center for Language & Speech Processing(CLSP), JHU
Related Courses
Machine Learning Capstone: An Intelligent Application with Deep LearningUniversity of Washington via Coursera Elaborazione del linguaggio naturale
University of Naples Federico II via Federica Deep Learning for Natural Language Processing
University of Oxford via Independent Deep Learning Summer School
Independent Sequence Models
DeepLearning.AI via Coursera